ecoscope.plotting

Submodules

• ecoscope.plotting.plot

Package Contents

class ecoscope.plotting.BarConfig

A class to represent configs for an individual bar in a bar chart. Attributes: ———- column : str

The name of the column to be used for the bar.

agg_funcstr

The aggregation function to be applied to the column data.

labelstr

The label for the bar.

styledict, optional

A dictionary containing style options for the individual bar (default is None).

column: str

agg_func: str

label: str

style: dict = None

class ecoscope.plotting.EcoPlotData(grouped, x_col='x', y_col='y', color_col=None, groupby_style=None, **style)

grouped

x_col = 'x'

y_col = 'y'

color_col = None

groupby_style

style

ecoscope.plotting.add_seasons(fig, season_df)

ecoscope.plotting.bar_chart(data, bar_configs, category, layout_kwargs=None)

Creates a bar chart from the provided dataframe :param data: The data to plot :type data: pd.DataFrame :param bar_configs: Specification for the bar chart, including labels, columns, and functions for aggregation. :type bar_configs: a list of BarConfigs :param category: The column name in the dataframe to group by and use as the x-axis categories. :type category: str :param layout_kwargs: Additional kwargs passed to plotly.go.Figure(layout) :type layout_kwargs: dict

Returns:

fig – The plotly bar chart

Return type:

plotly.graph_objects.Figure

Parameters:

• data (pandas.DataFrame)

• bar_configs (list[BarConfig])

• category (str)

• layout_kwargs (dict)

ecoscope.plotting.ecoplot(data, title='', out_path=None, subplot_height=100, subplot_width=700, vertical_spacing=0.001, annotate_name_pos=(0.01, 0.99), y_title_2=None, layout_kwargs=None, tickformat='%b-%Y', **make_subplots_kwargs)

ecoscope.plotting.line_chart(data, x_column, y_column, category_column=None, line_kwargs=None, layout_kwargs=None)

Creates a line chart from the provided dataframe :param data: The data to plot :type data: pd.DataFrame :param x_column: The name of the dataframe column to pull x-axis values from :type x_column: str :param y_column: The name of the dataframe column to pull y-axis values from :type y_column: str :param category_column: The column name in the dataframe to group by and use as separate traces. :type category_column: str :param line_kwargs: Line style kwargs passed to plotly.go.Scatter() :type line_kwargs: dict :param layout_kwargs: Additional kwargs passed to plotly.go.Figure(layout) :type layout_kwargs: dict

Returns:

fig – The plotly line chart

Return type:

plotly.graph_objects.Figure

Parameters:

• data (pandas.DataFrame)

• x_column (str)

• y_column (str)

• category_column (str)

• line_kwargs (dict)

• layout_kwargs (dict)

ecoscope.plotting.mcp(relocations)

ecoscope.plotting.nsd(relocations)

ecoscope.plotting.pie_chart(data, value_column, label_column=None, color_column=None, style_kwargs=None, layout_kwargs=None)

Creates a pie chart from the provided dataframe :param data: The data to plot :type data: pd.Dataframe :param value_column: The name of the dataframe column to pull slice values from

If the column contains non-numeric values, it is assumed to be categorical

and the pie slices will be a count of the occurrences of the category

Parameters:

• label_column (str) – The name of the dataframe column to label slices with, required if the data in value_column is numeric

• style_kwargs (dict) – Additional style kwargs passed to go.Pie()

• layout_kwargs (dict) – Additional kwargs passed to plotly.go.Figure(layout)

• data (pandas.DataFrame)

• value_column (str)

• color_column (str | None)

Returns:

fig – The plotly bar chart

Return type:

plotly.graph_objects.Figure

ecoscope.plotting.plot_seasonal_dist(ndvi_vals, cuts, bandwidth=0.05, output_file=None)

ecoscope.plotting.speed(trajectory)

ecoscope.plotting.stacked_bar_chart(data, agg_function, stack_column, layout_kwargs=None)

Creates a stacked bar chart from the provided EcoPlotData object :param data: The data to plot, counts categorical data.y_col values for data.x_col :type data: ecoscope.Plotting.EcoPlotData :param agg_function: The pandas.Dataframe.aggregate() function to run ie; ‘count’, ‘sum’ :type agg_function: str :param stack_column: The name of the column in the data to build stacks from, should be categorical :type stack_column: str :param layout_kwargs: Additional kwargs passed to plotly.go.Figure(layout) :type layout_kwargs: dict

Returns:

fig – The plotly bar chart

Return type:

plotly.graph_objects.Figure

Parameters:

• data (EcoPlotData)

• agg_function (str)

• stack_column (str)

• layout_kwargs (dict)